Prediction

Is the French football team doomed to fail again at the World Cup?

Dr Nicolas Scelles

Posted: June 8, 2014

As written by Julien Guyon in his very interesting working paper[i], several media talked about a ‘potgate’ for the draw of the 2014 FIFA World Cup BrazilTM according to which France would have been favoured. The objective is not to question the reality of the ‘potgate’ but rather the idea that France has an easy group. This is based on FIFA ranking which is open to criticism. Indeed, its calculation includes arbitrary choices: an arbitrary choice of years considered (current and last three years), an arbitrary weighting of year importance (100% for year n, 50% for year n-1, 30% for year n-2 and 20% for year n-3), an arbitrary weighting of match importance and an arbitrary weighting of confederation strength based on the last three World CupTM competitions. These arbitrary choices are certainly unavoidable and it is not question here to criticize FIFA.

I want to suggest another approach to consider relative team strengths – also open to criticism but allowing us to have an alternative. I did a regression on games including at least one team qualified for the World CupTM over the period 08/2012-12/2013 (514 games). This regression looked at explaining goal differences between teams by home advantage and dummies for teams. For example, if Brazil is the first team, I put 1; if Brazil is the second team, I put -1; if Brazil is not implied, I put 0. I reproduced this for every team. The model explains 67% of total variation of outcomes, what is good but obviously not perfect. It provides a hierarchy among teams that is different to FIFA ranking (the one considered for the draw of the 2014 World Cup BrazilTM is indicated into brackets): 1) Brazil (11), 2) Argentina (3), 3) Colombia (4), 4) Spain (1), 5) Germany (2), 6) Ecuador (21), 7) Chile (12), 8) Bosnia (16), 9) France (20), 10) Russia (19), 11) Netherlands (9), 12) Uruguay (6), 13) Portugal (14), 14) Italy (8), 15) Belgium (5), 16) Switzerland (7), 17) England (10), 18) United States (13), 19) Nigeria (26), 20) Ivory Coast (17), 21) Croatia (18), 22) Greece (15), 23) Mexico (23), 24) Honduras (27), 25) Costa Rica (24), 26) Japan (28), 27) Cameroon (32), 28) Algeria (25), 29) Ghana (22), 30) Iran (29), 31) South Korea (30), 32) Australia (31).

Let’s consider competitive balance within and between groups. With FIFA ranking, the hierarchy from the strongest to the weakest group is as follows (average ranking is indicated into brackets):

1) D with Uruguay / Costa Rica / Italy / England (12)

2) G with Germany / Ghana / United States / Portugal (12.75)

3) B with Spain / Chile / Australia / Netherlands (13.25)

4) C with Colombia / Ivory Coast / Japan / Greece (16)

5) F with Argentina / Nigeria / Iran / Bosnia (18.5)

6) E with Switzerland / Ecuador / Honduras / France (18.75)

7) H with Belgium / Algeria / South Korea / Russia (19.75)

8) A with Brazil / Cameroon / Mexico / Croatia (21).

Now, with my regression ranking, the hierarchy becomes as follows: 1) B (13.5), 2) E (13.75), 3) F (14.75), 4) G (16.25), 5) D (17), 6) C (17.75), 7) A (18), 8) H (21). It means that France would be in a difficult and not an easy group whereas England and United States would be in a balanced and not a difficult group. It is fair to specify that the better average ranking in Group E with my regression is partially due to the better ranking for France (from 20 to 9) and perhaps the average ranking of the other teams in Group E is the same with FIFA ranking and my regression, what would mean that games for France are as difficult with FIFA ranking as with my regression. Nevertheless, when I delete France to calculate the average ranking in Group E, I get 18.33 with FIFA ranking and 15.33 with my regression. Consequently, games for France are more difficult with my regression than with FIFA ranking. Finally, the ‘potgate’ was perhaps not so favourable for France!

IGuyon, Julien, Rethinking the FIFA World Cup Final Draw (April 12, 2014). Available at SSRN: [Link] or [Link]

About Dr Nicola Scelles

Nicolas Scelles is lecturer at the School of Sport, Stirling University, Scotland. He holds a PhD in sports economics from the University of Caen Basse-Normandie, France. He has articles in international journals including Applied Economics, Economics Bulletin, International Journal of Sport Finance and International Journal of Sport Management and Marketing.